The finance industry has long relied on statistical models, which made it a natural early adopter of more advanced AI techniques as they became available.
Fraud Detection
Banks use AI models trained on transaction patterns to spot unusual activity in real time, flagging potentially fraudulent transactions far faster and more accurately than rule-based systems could manage.
Credit Scoring
Lenders increasingly use AI models to assess creditworthiness by analysing a broader range of financial data points than traditional credit scores alone, though this practice also raises fairness questions that regulators are actively working to address.
Algorithmic Trading
Trading firms use AI systems to analyse market data and execute trades at speeds far beyond human capability, identifying patterns across vast amounts of financial information in real time.
Customer-Facing Tools
Many banking apps now include AI-powered budgeting insights and chatbots that can answer account questions instantly, making everyday banking more convenient for customers.
Because financial decisions carry serious consequences for individuals, most AI systems in this space operate under significant regulatory oversight, with human review remaining a legal requirement for many high-stakes decisions.